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da142bc 24f0bf0 da142bc | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 245 246 247 248 249 250 251 252 253 254 255 256 257 258 259 260 261 262 263 264 265 266 267 268 269 270 271 272 273 274 275 276 277 278 279 280 281 282 283 284 285 286 287 288 289 290 291 292 293 294 295 296 297 298 299 300 301 302 303 304 305 306 307 308 309 310 311 312 313 314 315 316 317 | """Comprehensive AI Provider Test Script
Tests NVIDIA, Groq, and Google Gemini providers with 10 different prompts.
"""
import asyncio
import json
import time
from datetime import datetime
from pathlib import Path
from app.config import get_settings
from app.models.router import SmartModelRouter, TaskType
# Test prompts covering different use cases
TEST_PROMPTS = [
{
"name": "Code Generation",
"prompt": "Write a Python function to calculate fibonacci numbers recursively.",
"task_type": TaskType.CODE,
"preferred_provider": "nvidia",
"preferred_model": "llama-3.3-70b",
},
{
"name": "Data Extraction",
"prompt": "Extract the key information from this text: 'John Doe, age 35, lives in New York and works as a software engineer at Tech Corp since 2020.'",
"task_type": TaskType.EXTRACTION,
"preferred_provider": "groq",
"preferred_model": "llama-3.3-70b-versatile",
},
{
"name": "Reasoning Task",
"prompt": "If a train travels 120 miles in 2 hours, and another train travels 180 miles in 3 hours, which train is faster and by how much?",
"task_type": TaskType.REASONING,
"preferred_provider": "nvidia",
"preferred_model": "devstral-2-123b",
},
{
"name": "General Question",
"prompt": "What are the three primary colors?",
"task_type": TaskType.GENERAL,
"preferred_provider": "groq",
"preferred_model": "llama-3.3-70b-versatile",
},
{
"name": "JSON Generation",
"prompt": "Generate a JSON object representing a user profile with name, email, age, and interests (array).",
"task_type": TaskType.CODE,
"preferred_provider": "nvidia",
"preferred_model": "devstral-2-123b",
},
{
"name": "Text Summarization",
"prompt": "Summarize in one sentence: Artificial intelligence is transforming industries by automating tasks, improving decision-making, and creating new opportunities for innovation.",
"task_type": TaskType.GENERAL,
"preferred_provider": "groq",
"preferred_model": "llama-3.3-70b-versatile",
},
{
"name": "Math Problem",
"prompt": "Solve: 2x + 5 = 15. Show your work.",
"task_type": TaskType.REASONING,
"preferred_provider": "nvidia",
"preferred_model": "llama-3.3-70b",
},
{
"name": "Creative Writing",
"prompt": "Write a haiku about coding at night.",
"task_type": TaskType.GENERAL,
"preferred_provider": "nvidia",
"preferred_model": "llama-3.3-70b",
},
{
"name": "Code Debug",
"prompt": "Find the bug in this code: def add(a, b): return a + b + 1",
"task_type": TaskType.CODE,
"preferred_provider": "groq",
"preferred_model": "llama-3.3-70b-versatile",
},
{
"name": "Complex Reasoning",
"prompt": "If all roses are flowers, and some flowers fade quickly, can we conclude that some roses fade quickly?",
"task_type": TaskType.REASONING,
"preferred_provider": "nvidia",
"preferred_model": "devstral-2-123b",
},
]
class TestReporter:
"""Test reporter for generating markdown reports."""
def __init__(self):
self.results = []
self.start_time = None
self.end_time = None
def start(self):
"""Mark test start time."""
self.start_time = datetime.now()
def end(self):
"""Mark test end time."""
self.end_time = datetime.now()
def add_result(self, test_case: dict, success: bool, response: str = None,
error: str = None, duration: float = 0, metadata: dict = None):
"""Add a test result."""
self.results.append({
"test_name": test_case["name"],
"prompt": test_case["prompt"],
"task_type": test_case["task_type"].value,
"preferred_provider": test_case.get("preferred_provider"),
"preferred_model": test_case.get("preferred_model"),
"success": success,
"response": response,
"error": error,
"duration_seconds": duration,
"metadata": metadata or {},
"timestamp": datetime.now().isoformat(),
})
def generate_markdown(self) -> str:
"""Generate markdown test report."""
total_tests = len(self.results)
passed = sum(1 for r in self.results if r["success"])
failed = total_tests - passed
success_rate = (passed / total_tests * 100) if total_tests > 0 else 0
total_duration = self.end_time - self.start_time if self.end_time and self.start_time else None
md = f"""# AI Provider Test Report
**Generated:** {datetime.now().strftime("%Y-%m-%d %H:%M:%S")}
**Test Duration:** {total_duration.total_seconds():.2f}s
## Summary
- **Total Tests:** {total_tests}
- **Passed:** ✅ {passed}
- **Failed:** ❌ {failed}
- **Success Rate:** {success_rate:.1f}%
## Test Results
"""
for i, result in enumerate(self.results, 1):
status = "✅ PASS" if result["success"] else "❌ FAIL"
md += f"### {i}. {result['test_name']} {status}\n\n"
md += f"**Task Type:** {result['task_type']} \n"
md += f"**Provider:** {result['preferred_provider']} \n"
md += f"**Model:** {result['preferred_model']} \n"
md += f"**Duration:** {result['duration_seconds']:.2f}s \n\n"
md += f"**Prompt:**\n```\n{result['prompt']}\n```\n\n"
if result["success"]:
md += f"**Response:**\n```\n{result['response'][:500]}{'...' if len(result['response']) > 500 else ''}\n```\n\n"
if result["metadata"]:
md += f"**Metadata:**\n"
for key, value in result["metadata"].items():
md += f"- {key}: {value}\n"
md += "\n"
else:
md += f"**Error:**\n```\n{result['error']}\n```\n\n"
md += "---\n\n"
# Provider summary
md += "## Provider Performance\n\n"
providers = {}
for result in self.results:
provider = result["preferred_provider"]
if provider not in providers:
providers[provider] = {"total": 0, "passed": 0, "total_duration": 0}
providers[provider]["total"] += 1
if result["success"]:
providers[provider]["passed"] += 1
providers[provider]["total_duration"] += result["duration_seconds"]
md += "| Provider | Tests | Passed | Failed | Success Rate | Avg Duration |\n"
md += "|----------|-------|--------|--------|--------------|-------------|\n"
for provider, stats in sorted(providers.items()):
success_rate = (stats["passed"] / stats["total"] * 100) if stats["total"] > 0 else 0
avg_duration = stats["total_duration"] / stats["total"] if stats["total"] > 0 else 0
md += f"| {provider} | {stats['total']} | {stats['passed']} | {stats['total'] - stats['passed']} | {success_rate:.1f}% | {avg_duration:.2f}s |\n"
return md
async def run_tests():
"""Run all test cases."""
print("="*80)
print("AI Provider Comprehensive Test Suite")
print("="*80)
print()
# Initialize settings and router
settings = get_settings()
print("Initializing model router...")
print(f" NVIDIA API Key: {'[SET]' if settings.nvidia_api_key else '[NOT SET]'}")
print(f" Groq API Key: {'[SET]' if settings.groq_api_key else '[NOT SET]'}")
print(f" Google API Key: {'[SET]' if settings.google_api_key else '[NOT SET]'}")
print()
router = SmartModelRouter(
openai_api_key=settings.openai_api_key,
anthropic_api_key=settings.anthropic_api_key,
google_api_key=settings.google_api_key,
groq_api_key=settings.groq_api_key,
nvidia_api_key=settings.nvidia_api_key,
)
await router.initialize()
available_providers = [p for p in router.providers.keys()]
print(f"Available providers: {', '.join(available_providers)}")
print()
reporter = TestReporter()
reporter.start()
# Run tests
for i, test_case in enumerate(TEST_PROMPTS, 1):
print(f"[{i}/{len(TEST_PROMPTS)}] Running: {test_case['name']}")
print(f" Provider: {test_case['preferred_provider']}")
print(f" Model: {test_case['preferred_model']}")
print(f" Task Type: {test_case['task_type'].value}")
start_time = time.time()
try:
response = await router.complete(
messages=[{"role": "user", "content": test_case["prompt"]}],
model=test_case.get("preferred_model"),
task_type=test_case["task_type"],
fallback=False, # No fallback - test only the requested model
max_tokens=500,
temperature=0.7,
)
duration = time.time() - start_time
if response and response.content:
print(f" [OK] Success ({duration:.2f}s)")
print(f" Response: {response.content[:100]}...")
reporter.add_result(
test_case=test_case,
success=True,
response=response.content,
duration=duration,
metadata={
"model_used": response.model,
"provider_used": response.provider,
"tokens": response.usage.total_tokens if response.usage else 0,
}
)
else:
print(f" [FAIL] Failed: Empty response")
reporter.add_result(
test_case=test_case,
success=False,
error="Empty response from provider",
duration=duration,
)
except Exception as e:
duration = time.time() - start_time
print(f" [FAIL] Failed ({duration:.2f}s): {str(e)}")
reporter.add_result(
test_case=test_case,
success=False,
error=str(e),
duration=duration,
)
print()
reporter.end()
# Generate report
print("="*80)
print("Generating test report...")
report_md = reporter.generate_markdown()
# Save report
report_path = Path("docs/test/ai-provider-test-report.md")
report_path.parent.mkdir(parents=True, exist_ok=True)
report_path.write_text(report_md, encoding="utf-8")
print(f"[OK] Report saved to: {report_path}")
print()
# Print summary
total = len(reporter.results)
passed = sum(1 for r in reporter.results if r["success"])
failed = total - passed
print("="*80)
print("TEST SUMMARY")
print("="*80)
print(f"Total Tests: {total}")
print(f"Passed: [OK] {passed}")
print(f"Failed: [X] {failed}")
print(f"Success Rate: {(passed/total*100):.1f}%")
print("="*80)
return passed == total
if __name__ == "__main__":
success = asyncio.run(run_tests())
exit(0 if success else 1)
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